DOC: Convert to markdown: torch.overrides.rst, type_info.rst, utils.rst, xpu.rst (#155088)

Fixes #155041

Pull Request resolved: https://github.com/pytorch/pytorch/pull/155088
Approved by: https://github.com/svekars

Co-authored-by: Svetlana Karslioglu <svekars@meta.com>

docs/source/torch.overrides.md

@@ -1,30 +1,49 @@
+```{eval-rst}
 .. currentmodule:: torch.overrides
+```
 
-torch.overrides
+# torch.overrides
----------------
+```{eval-rst}
 .. py:module:: torch.overrides
+```
 
 This module exposes various helper functions for the ``__torch_function__``
-protocol. See :ref:`extending-torch-python` for more details on the
+protocol. See {ref}`extending-torch-python` for more details on the
 ``__torch_function__`` protocol.
 
-Functions
+## Functions
-~~~~~~~~~
+```{eval-rst}
-
 .. autofunction::  get_ignored_functions
+```
 
+```{eval-rst}
 .. autofunction::  get_overridable_functions
+```
 
+```{eval-rst}
 .. autofunction::  resolve_name
+```
 
+```{eval-rst}
 .. autofunction::  get_testing_overrides
+```
 
+```{eval-rst}
 .. autofunction::  handle_torch_function
+```
 
+```{eval-rst}
 .. autofunction::  has_torch_function
+```
 
+```{eval-rst}
 .. autofunction::  is_tensor_like
+```
 
+```{eval-rst}
 .. autofunction::  is_tensor_method_or_property
+```
 
+```{eval-rst}
 .. autofunction::  wrap_torch_function
+```

docs/source/type_info.md

@@ -0,0 +1,61 @@
+```{eval-rst}
+.. currentmodule:: torch
+```
+
+(type-info-doc)=
+# Type Info
+
+The numerical properties of a {class}`torch.dtype` can be accessed through either the {class}`torch.finfo` or the {class}`torch.iinfo`.
+
+(finfo-doc)=
+## torch.finfo
+
+```{eval-rst}
+.. class:: torch.finfo
+```
+
+A {class}`torch.finfo` is an object that represents the numerical properties of a floating point
+{class}`torch.dtype`, (i.e. ``torch.float32``, ``torch.float64``, ``torch.float16``, and ``torch.bfloat16``).
+This is similar to [numpy.finfo](https://numpy.org/doc/stable/reference/generated/numpy.finfo.html).
+
+A {class}`torch.finfo` provides the following attributes:
+
+| Name            | Type  | Description                                                                |
+| :-------------- | :---- | :------------------------------------------------------------------------- |
+| bits            | int   | The number of bits occupied by the type.                                   |
+| eps             | float | The smallest representable number such that ``1.0 + eps != 1.0``.          |
+| max             | float | The largest representable number.                                          |
+| min             | float | The smallest representable number (typically ``-max``).                    |
+| tiny            | float | The smallest positive normal number. Equivalent to ``smallest_normal``.    |
+| smallest_normal | float | The smallest positive normal number. See notes.                            |
+| resolution      | float | The approximate decimal resolution of this type, i.e., ``10**-precision``. |
+
+```{note}
+  The constructor of {class}`torch.finfo` can be called without argument,
+  in which case the class is created for the pytorch default dtype (as returned by {func}`torch.get_default_dtype`).
+```
+
+```{note}
+  `smallest_normal` returns the smallest *normal* number, but there are smaller
+  subnormal numbers. See https://en.wikipedia.org/wiki/Denormal_number
+  for more information.
+```
+
+(iinfo-doc)=
+## torch.iinfo
+
+```{eval-rst}
+.. class:: torch.iinfo
+```
+
+A {class}`torch.iinfo` is an object that represents the numerical properties of a integer
+{class}`torch.dtype` (i.e. ``torch.uint8``, ``torch.int8``, ``torch.int16``, ``torch.int32``, and ``torch.int64``).
+This is similar to [numpy.iinfo](https://numpy.org/doc/stable/reference/generated/numpy.iinfo.html).
+
+A {class}`torch.iinfo` provides the following attributes:
+
+| Name | Type | Description                              |
+| :--- | :--- | :--------------------------------------- |
+| bits | int  | The number of bits occupied by the type. |
+| max  | int  | The largest representable number.        |
+| min  | int  | The smallest representable number.       |

docs/source/type_info.rst

@@ -1,62 +0,0 @@
-.. currentmodule:: torch
-
-.. _type-info-doc:
-
-Type Info
-=========
-
-The numerical properties of a :class:`torch.dtype` can be accessed through either the :class:`torch.finfo` or the :class:`torch.iinfo`.
-
-.. _finfo-doc:
-
-torch.finfo
------------
-
-.. class:: torch.finfo
-
-A :class:`torch.finfo` is an object that represents the numerical properties of a floating point
-:class:`torch.dtype`, (i.e. ``torch.float32``, ``torch.float64``, ``torch.float16``, and ``torch.bfloat16``). This is similar to `numpy.finfo <https://numpy.org/doc/stable/reference/generated/numpy.finfo.html>`_.
-
-A :class:`torch.finfo` provides the following attributes:
-
-===============        =====   ==========================================================================
-Name                   Type    Description
-===============        =====   ==========================================================================
-bits                   int     The number of bits occupied by the type.
-eps                    float   The smallest representable number such that ``1.0 + eps != 1.0``.
-max                    float   The largest representable number.
-min                    float   The smallest representable number (typically ``-max``).
-tiny                   float   The smallest positive normal number. Equivalent to ``smallest_normal``.
-smallest_normal        float   The smallest positive normal number. See notes.
-resolution             float   The approximate decimal resolution of this type, i.e., ``10**-precision``.
-===============        =====   ==========================================================================
-
-.. note::
-  The constructor of :class:`torch.finfo` can be called without argument, in which case the class is created for the pytorch default dtype (as returned by :func:`torch.get_default_dtype`).
-
-.. note::
-  `smallest_normal` returns the smallest *normal* number, but there are smaller
-  subnormal numbers. See https://en.wikipedia.org/wiki/Denormal_number
-  for more information.
-
-
-.. _iinfo-doc:
-
-torch.iinfo
-------------
-
-.. class:: torch.iinfo
-
-
-A :class:`torch.iinfo` is an object that represents the numerical properties of a integer
-:class:`torch.dtype` (i.e. ``torch.uint8``, ``torch.int8``, ``torch.int16``, ``torch.int32``, and ``torch.int64``). This is similar to `numpy.iinfo <https://numpy.org/doc/stable/reference/generated/numpy.iinfo.html>`_.
-
-A :class:`torch.iinfo` provides the following attributes:
-
-=========   =====   ========================================
-Name        Type    Description
-=========   =====   ========================================
-bits        int     The number of bits occupied by the type.
-max         int     The largest representable number.
-min         int     The smallest representable number.
-=========   =====   ========================================

docs/source/utils.md

@@ -1,8 +1,13 @@
-torch.utils
+# torch.utils
-===================================
+```{eval-rst}
 .. automodule:: torch.utils
-.. currentmodule:: torch.utils
+```
 
+```{eval-rst}
+.. currentmodule:: torch.utils
+```
+
+```{eval-rst}
 .. autosummary::
     :toctree: generated
     :nosignatures:
@@ -12,9 +17,11 @@ torch.utils
     get_cpp_backtrace
     set_module
     swap_tensors
+```
 
-.. This module needs to be documented. Adding here in the meantime
+<!-- This module needs to be documented. Adding here in the meantime
-.. for tracking purposes
+for tracking purposes -->
+```{eval-rst}
 .. py:module:: torch.utils.backend_registration
 .. py:module:: torch.utils.benchmark.examples.compare
 .. py:module:: torch.utils.benchmark.examples.fuzzer
@@ -87,3 +94,4 @@ torch.utils
 .. py:module:: torch.utils.tensorboard.writer
 .. py:module:: torch.utils.throughput_benchmark
 .. py:module:: torch.utils.weak
+```

docs/source/xpu.md

@@ -1,8 +1,12 @@
-torch.xpu
+# torch.xpu
-===================================
+```{eval-rst}
 .. automodule:: torch.xpu
+```
+```{eval-rst}
 .. currentmodule:: torch.xpu
+```
 
+```{eval-rst}
 .. autosummary::
     :toctree: generated
     :nosignatures:
@@ -26,9 +30,10 @@ torch.xpu
     set_stream
     stream
     synchronize
+```
 
-Random Number Generator
+## Random Number Generator
--------------------------
+```{eval-rst}
 .. autosummary::
     :toctree: generated
     :nosignatures:
@@ -42,21 +47,27 @@ Random Number Generator
     seed_all
     set_rng_state
     set_rng_state_all
+```
 
-Streams and events
+## Streams and events
-------------------
+```{eval-rst}
 .. autosummary::
     :toctree: generated
     :nosignatures:
 
     Event
     Stream
+```
 
+```{eval-rst}
 .. automodule:: torch.xpu.memory
+```
+```{eval-rst}
 .. currentmodule:: torch.xpu.memory
+```
 
-Memory management
+## Memory management
------------------
+```{eval-rst}
 .. autosummary::
     :toctree: generated
     :nosignatures:
@@ -71,9 +82,11 @@ Memory management
      memory_stats_as_nested_dict
      reset_accumulated_memory_stats
      reset_peak_memory_stats
+```
 
-
+<!-- This module needs to be documented. Adding here in the meantime
-.. This module needs to be documented. Adding here in the meantime
+for tracking purposes -->
-.. for tracking purposes
+```{eval-rst}
 .. py:module:: torch.xpu.random
 .. py:module:: torch.xpu.streams
+```